74 research outputs found

    The Climate-system Historical Forecast Project: providing open access to seasonal forecast ensembles from centers around the globe

    Get PDF
    Fil: Tompkins, Adrian M.. The Abdus Salam; ItaliaFil: Ortiz de Zarate, Maria Ines. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la AtmĂłsfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la AtmĂłsfera; Argentina. Centre National de la Recherche Scientifique; FranciaFil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la AtmĂłsfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la AtmĂłsfera; Argentina. Centre National de la Recherche Scientifique; FranciaFil: Vera, Carolina. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Oficina de CoordinaciĂłn Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la AtmĂłsfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la AtmĂłsfera; Argentina. Centre National de la Recherche Scientifique; FranciaFil: Saulo, Andrea Celeste. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; Argentina. Ministerio de Defensa. Secretaria de Planeamiento. Servicio MeteorolĂłgico Nacional; ArgentinaFil: Merryfield, William J.. Canadian Centre for Climate Modelling and Analysis; CanadĂĄFil: Sigmond, Michael. Canadian Centre for Climate Modelling and Analysis; CanadĂĄFil: Lee, Woo Sung. Canadian Centre for Climate Modelling and Analysis; CanadĂĄFil: Baehr, Johanna. Universitat Hamburg; AlemaniaFil: Braun, Alain. MĂ©tĂ©o-France; FranciaFil: Amy Butler. National Ocean And Atmospheric Administration; Estados UnidosFil: DĂ©quĂ©, Michel. MĂ©tĂ©o-France; FranciaFil: Doblas Reyes, Francisco J.. InstituciĂł Catalana de Recerca i Estudis Avancats; España. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; EspañaFil: Gordon, Margaret. Met Office; Reino UnidoFil: Scaife, Adam A.. University of Exeter; Reino UnidoFil: Yukiko Imada. Japan Meteorological Agency. Meteorological Research Institute. Climate Research Department; JapĂłnFil: Masayoshi Ishii. Japan Meteorological Agency. Meteorological Research Institute. Climate Research Department; JapĂłnFil: Tomoaki Ose. Japan Meteorological Agency. Meteorological Research Institute. Climate Research Department; JapĂłnFil: Kirtman, Ben. University of Miami; Estados UnidosFil: Kumar, Arun. National Ocean And Atmospheric Administration; Estados UnidosFil: MĂŒller, Wolfgang A.. Max-Planck-Institut fĂŒr Meteorologie; AlemaniaFil: Pirani, Anna. UniversitĂ© Paris-Saclay; FranciaFil: Stockdale, Tim. European Centre for Medium-Range Weather; Reino UnidoFil: Rixen, Michel. World Meteorological Organization. World Climate Research Programme; SuizaFil: Yasuda, Tamaki. Japan Meteorological Agency. Climate Prediction Division; JapĂł

    Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

    Get PDF
    BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

    Country-level gender inequality is associated with structural differences in the brains of women and men

    Get PDF
    ç”·ć„łé–“ăźäžćčłç­‰ăšè„łăźæ€§ć·ź --ç”·ć„łé–“ăźäžćčłç­‰ăŻè„łæ§‹é€ ăźæ€§ć·źăšé–ąé€Łă™ă‚‹--. äșŹéƒœć€§ć­Šăƒ—ăƒŹă‚čăƒȘăƒȘăƒŒă‚č. 2023-05-10.Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women’s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7, 876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women’s brains and provide initial evidence for neuroscience-informed policies for gender equality

    Brain clocks capture diversity and disparities in aging and dementia

    Get PDF
    Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (RÂČ = 0.37, FÂČ = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.</p

    Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

    Get PDF
    Peer reviewe

    Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

    Get PDF
    The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)
    • 

    corecore